Does Emotional Intelligence Predict Persistence among Students on Academic Probation

Sylvia L. Mendez, Ph.D.

University of Colorado Colorado Springs

Carrie Arnold, Ph.D.

University of Colorado Colorado Springs

Patty Erjavec, Ph.D.

Pueblo Community College

Leona Lopez, Ph.D.

Pikes Peak Community College

Abstract

This study examines the influence of emotional intelligence (EI) on persistence among students on academic probation utilizing the Multi-Health Systems EQ-i 2.0 Higher Education Assessment. Binary logistic regression was used to determine the manner in which EI and other student-level variables of interest affect the likelihood of college students’ persistence to the following semester. When holding all other independent variables constant, the regression results found the intrapersonal domain of EI is a significant predictor of the likelihood of persistence. The intrapersonal domain includes dimensions related to self-regard, emotional self-awareness, assertiveness, independence, and self-actualization. This domain is an essential element in student development, as it relates to a student’s view of self and can be improved by focusing on developing one’s individuality, boundary setting, and communication skills. For higher education institutions to enhance the EI skills of their student body, particularly for those most at risk for departing the institution, a redistribution of resources is needed to address holistically the non-cognitive measures that influence persistence, retention, and overall student success.

Keywords: academic probation, at risk, emotional intelligence, persistence

The dynamics of student retention are changing rapidly and outpacing college and university resources as institutions have become increasingly dependent upon enrolling students who may be unprepared academically, financially, and emotionally for higher education (Fowles, 2014; Selingo, 2013). Higher education institutions are realizing the responsibility to serve all students, and particularly those with varied levels of preparedness, so they are turning their attention to both cognitive and non-cognitive approaches to retain students. Traditional academic interventions, such as academic advising and tutoring services that target cognitive abilities, are being complemented with first-year programming, mental health counseling, and peer mentoring to enhance non-cognitive abilities, such as emotional intelligence (EI) (DeAngelo, 2014; Permzadian & Credé, 2016; Tinto, 2012; Whiteman, Barry, Mroczek, & MacDermid Wadsworth, 2013).

The role of EI in one’s life was popularized by Daniel Goleman’s (1995) Emotional Intelligence: Why it Can Matter More than IQ. He outlined EI as the self-awareness, self-regulation, social skills, empathy, and motivation competencies and skills that drive performance. It is defined as, “A set of emotional and social skills that influence the way we perceive and express ourselves, develop and maintain social relationships, cope with challenges, and use emotional information in an effective and meaningful way” (Multi-Health Systems [MHS], 2011, p. 1). In applying EI to higher education, students who understand and successfully manage their emotions may possess the skills necessary to perform better academically and to be more socially prepared for success in the postsecondary education environment (Keefer, Parker, & Saklofske, 2018; Stein, Book, & Kanoy, 2013). This study considers this supposition by examining the influence of EI on persistence among students on academic probation utilizing the MHS EQ-i 2.0 Higher Education Assessment. The EQ-i 2.0 is one of the only EI assessments designed specifically for use with college students.

According to the National Center for Education Statistics, the national six-year graduation rate for first-time, full-time undergraduate students in 2015-2016 was 59.8% at four-year institutions, while the retention rate for first-time students was 80.8% (McFarland et al., 2018). Morrow and Ackermann (2012) reported “approximately 35% of students depart a university because of academic reasons; the other 65% leave for non-academic reasons” (p. 483). These percentages highlight the effect of non-cognitive factors, such as EI, on the academic success and dropout rates of students, which cannot be remedied by cognitive interventions alone (Gerdes & Mallinckrodt, 1994; Habley, Bloom, & Robbins, 2012; Hartley, 2011; Keefer et al., 2018; Parker, Hogan, Eastabrook, Oke, & Wood, 2006; Tinto, 2012). Colleges and universities often support students on academic probation with academic skill building, but theories of EI have brought attention to the “whole” student, which include reasoning capabilities, creativity, emotions, and interpersonal skills (Stein et al., 2013). The development of EI skills may be beneficial in helping students regain satisfactory academic standing (Afolabi, Ogunmwonyi, & Okediji, 2009; Friedlander, Reid, Shupak, & Cribbie, 2007; Ridgell & Lounsbury, 2004). In an effort to improve retention rates, assessing and developing students’ EI may help them to better understand and effectively manage their emotions.

Purpose of the Study

Considerable research has been conducted relative to EI and its possible influence on student success and overall adjustment to college life (Afolabi et al., 2009; Keefer et al., 2018; Keefer, Parker, & Wood, 2012; Mega, Ronconi, & De Beni, 2014; Noor & Hanafi, 2017; Parker et al., 2006). This empirical evidence has challenged the age-old notion that cognitive ability alone is responsible for academic success; it is conceivable that new and successful methods for increasing persistence and retention rates can be accomplished by attending to non-cognitive factors of collegiate life. The purpose of this cross-sectional survey study is to examine the influence of EI on persistence among students on academic probation for the first time utilizing the MHS EQ-i 2.0 Higher Education Assessment. A binary logistic regression was performed to determine the manner in which EI affects the likelihood of college students’ persistence to the following semester while controlling for student-level variables of interest. This form of regression was appropriate because the dependent variable of persistence is binary/dichotomous; students either persisted to the next semester at the institution or they departed. The research question for this study is: Does EI increase the likelihood of persistence among students on academic probation?

Literature Review

As institutions of higher education are pressured to increase retention rates among students who struggle academically, they are turning to cognitive and non-cognitive methods to do so (DeAngelo, 2014; Fowles, 2014; Selingo, 2013; Tinto, 2012). Concerns regarding academic performance are not new; however, specific consideration is now devoted to the prediction of college persistence among students at risk for dropping out due to unsatisfactory grades (Balduf, 2009; Bryant & Malone, 2015; Ishitani, 2006; Mega et al., 2014; Moore, 2004; Pritchard & Wilson, 2003). Low grades can be a direct result of academic difficulty or unpreparedness, although often they are an outcome of a myriad of factors including poor campus integration, financial struggles, personal and family issues, as well as a lack of responsiveness from higher education institutions to systematically address these student realities (Keefer et al., 2012; Mega et al., 2014; Tinto, 2012). Awareness of non-cognitive factors is invaluable to postsecondary institutions that seek to lower attrition rates and may aid in the creation of programs to assist students who struggle to adjust to collegiate life (DeAngelo, 2014; Tinto, 2012). Tinto (2012) emphasized both academic and social cultural integration as the most important factors in college retention and persistence, as students who are not assimilated into classroom and institutional cultures are more likely to struggle academically and, ultimately, leave higher education altogether.

Researchers have found students with high EI are more self-assured and transition through college with a greater degree of academic success (Afolabi et al., 2009; Keefer et al., 2018; Keefer et al., 2012; Parker et al., 2006; Salovey, Mayer, Goldman, Turvey, & Palfai, 1995). Keefer et al. (2012) compared GPA, age, and course load of students and found that those with high EI were more likely to graduate than those with lower levels of EI. It also has been suggested that a strong level of EI aids in psychological functioning and overall mental health and wellness (Keefer et al., 2018; Keefer et al., 2012; Morales, 2008; Noor & Hanafi, 2017; Parker et al., 2006; Ruiz-Aranda et al., 2012; Saklofske, Austin, Mastoras, Beaton, & Osborne, 2012). This theory has been supported by Houghton, Wu, Godwin, Neck, and Manz (2012), who found the ability to manage and to interpret one’s emotional processes is a key component of EI, particularly when stressed with academic difficulties.

Additionally, Morales (2008) found that “emotional intelligence is a core attribute of resilient individuals and is prominently displayed in how students have coped with the stress inherent in their academic journeys” (p. 166). Further, he purported that a student who demonstrates high EI exhibits the ability to (a) self-motivate and persist when challenged and frustrated, (b) control impulse and selfish indulgence, (c) regulate mood and keep distress from clouding the ability to think, and (d) be compassionate and hopeful. Singh and Sharma (2012) added: “A growing body of research has found a wide range of important life outcomes … are not adequately predicted by traditional measures of cognitive intelligence but can be predicted by emotional intelligence” (p. 108). In order to support EI efforts, colleges and universities are allocating resources toward the development of a sense of connectedness and belonging through the use of mentoring, first-year interest groups, and counseling programs to actively incorporate students into college life through co- and extra-curricular activities (Balduf, 2009; DeAngelo, 2014; Permzadian & Credé, 2016; Quaye & Harper, 2015; Tinto, 2012).

Other researchers, however, have found little or no correlation between EI and measures of academic success (Bastian, Burns, & Nettelbeck, 2005; Newsome, Day, & Catano, 2000). Some studies have found lower than expected EI scores for college students, leading to the possible conclusion that those entering higher education have insufficient life experiences for mature EI (Leedy & Smith, 2012). Nowack (2012) reported EI results are further complicated by the multiple models commonly recognized in the literature. At least four exist based on (a) trait, (b) competency, (c) mental ability, and (d) personality. Accordingly, various instruments are used to measure EI and the emotional-social competencies for each model. Some of the measurements do not overlap, while others appear to assess similar or identical aspects of this broad concept (Nowack, 2012). Thus, EI measured with various theoretical frameworks and measurement models yields differences that lead to contradictory findings in the literature on its role in academic success (Parker et al., 2006). Sparkman, Maulding, and Roberts (2012) suggested the need for additional research to determine the effects of education on EI and its use in higher education. Much remains to be studied about EI and its effect on academic persistence; it is essential to the future of college student success to explore its role, as it may potentially engage and motivate students academically.

Method

Research Design

A cross-sectional survey design was utilized to examine whether EI is a predictor of persistence among students on academic probation for the first time as it allows one to make inferences about a population of interest at one point in time (Fowler, 2013). The survey allowed for a descriptive and predictive exploration of EI as measured by the EQ-i 2.0 Higher Education Assessment, with special attention to the five EQ-i domains of intrapersonal, interpersonal, stress management, adaptability, and general mood. The research question for this study was:

Does EI increase the likelihood of persistence among students on academic probation?

Research Site

This study was conducted at a comprehensive, public university in the Mountain West. The university is categorized as a mixed residential-commuter campus and is one of the fastest growing institutions in the country. The student body includes nearly 20% students of color and an almost equal female-to-male ratio. Additionally, 30% are eligible for Federal Pell Grants and nearly 80% receive some form of financial aid.

Procedures

The research site’s Institutional Review Board granted permission to pursue this study with a sample of all students enrolled in a course designed for those on academic probation (students who attempted at least 12 credit hours and whose cumulative GPA falls below 2.0 are placed on academic probation). The course focuses on enhancing college success skills, such as understanding one’s learning style, developing effective study habits, and improving time management skills, as well as connecting with university academic resources and cocurricular activities. Course instructors offered extra-credit points for students to participate in this study. They were asked to submit their consent forms, to complete the EQ-i assessment (emailed to them and administered through MHS), and to participate in a debriefing session with a certified EQ-i coach. The debriefing sessions were held to review the EI assessment results with the students and to guide them to connect the way in which the EI dimensions intersect with their strengths and areas for enrichment. Ultimately, the sessions combined advising and coaching techniques in discussing ways to change their learned negative EI behaviors and to increase their EI agency to improve their overall well-being.

Sample

All 134 students who were on academic probation for the first time and who were enrolled in an academic probation course were invited to participate in this study; thus, a non-randomized, criterion-based sampling method was utilized (Patton, 2014). Eighty-eight of the 134 eligible students completed the EQ-i assessment. Of those, 69 submitted their consent form and met with an EQ-i coach to debrief their results, reducing the sample to 69 cases (51% response rate). The final sample included an almost equal female-to-male ratio, approximately 80% were White, the average age was 19, and 89% were first-year college students. The average high school GPA was 2.62 (SD = 0.597), and 93% were in-state residents. Nearly half worked while attending the university. The mean completion rate of spring courses was 13 credits (SD = 2.495), and the mean spring term GPA was 2.67 (SD = 0.746).

Measure: EQ-i 2.0 Higher Education Assessment

The growing body of EI research in colleges and universities has utilized the MHS EQ-i 2.0 Higher Education Assessment. The assessment is a 133-item self-report inventory based on five specific domains and 15 corresponding sub-scales: intrapersonal (self-regard, emotional self-expression, assertiveness, independence, self-actualization); interpersonal (empathy, social responsibility, interpersonal relationships); stress management (stress tolerance, impulse control); adaptability (reality testing, flexibility, problem solving); and general mood (optimism, happiness). The items are scored on a five-point scale with anchors of never/rarely to always/almost always. According to the MHS EQ-i 2.0 results scale, an overall EQ-i score, domain score, and sub-scale score between 60 and 89 is considered low and indicates the student requires enrichment. The range of 90-119 notes effective functioning, and 120-150 suggests enhanced functioning.

The MHS EQ-i 2.0 remains one of the primary methods of assessing EI with college students and has been recognized as a valuable tool in determining an individual’s ability to succeed academically (Dawda & Hart, 2000). This EI assessment was selected and utilized for the study based upon its reliability and validity. The overall internal consistency coefficient for the EQ-i is .97 with the North American normative sample, and the assessment has been shown to demonstrate high correlations with other social-emotional measurements (Bar-On, 2006). Additionally, the instrument is recognized by the Consortium for Research on Emotional Intelligence in Organizations and is the only EI assessment included in The Twentieth Mental Measurements Yearbook (Carlson, Geisinger, & Jonson, 2017), thereby demonstrating its extensive review and credibility for use.

Outcome Variable: Persistence

The outcome variable for this study was persistence, defined as a student’s continued enrollment into the next semester at the university (87% of the sample). For all first-time students on academic probation and enrolled in an academic probation course, 60% were retained; thus, an increased persistence rate was found among those on academic probation who participated in this study versus those who did not.

Explanatory Variable: EQ-i

The primary explanatory variable of interest was the EQ-i domain scores. The electronically generated raw scores were changed to standard scores with a mean of 100 and a standard deviation of 15 (MHS, 2011). Descriptive data of the overall EQ-i scores, domain scores, and sub-scale scores are included in Table 1. Overall, students in the sample scored in the low- to mid-range of effective functioning on each measure of EI, with lower levels of reality testing, problem solving, and optimism, and higher levels of interpersonal relationships, impulse control, and happiness.

Controlled Independent Variables

A number of other independent variables previously found to be predictors of persistence were included in this study: gender, ethnicity, GPA, credits completed, and academic status (freshman, sophomore, junior, and senior) (Afolabi et al., 2009; Balduf, 2009; Ishitani, 2006; Keefer et al., 2012; Moore, 2004; Parker et al., 2006). These variables were included in the model to control for variance, with EQ-i serving as the explanatory variable of the model. Gender (female or male) and ethnicity (White student or student of color) were treated as dichotomous variables, whereas GPA, credits completed, academic status, and EQ-i domain scores were treated as continuous variables.

Table 1: EQ-i Data

  M SD
TOTAL EQ-i Score 93.80 15.938
Intrapersonal Domain 95.07 16.494
      Self-Regard 98.03 15.911
      Emotional Self-Awareness 95.67 16.135
 Assertiveness 99.90 15.569
      Independence 92.77 16.603
      Self-Actualization 96.86 15.256
Interpersonal Domain 97.49 15.400
      Empathy 95.62 16.409
      Social Responsibility 95.83 15.565
      Interpersonal Relationships 100.20 14.874
Stress Management Domain 97.88 13.875
      Stress Tolerance 94.19 15.089
      Impulse Control 101.07 15.207
Adaptability Domain 92.13 15.944
      Reality Testing 90.86 15.021
      Flexibility 98.90 16.466
      Problem Solving 91.13 16.224
General Mood Domain 97.06 14.402
      Optimism 91.67 15.549
      Happiness 101.84 14.222

Note. M = Mean; SD = Standard Deviation.

Statistical Analysis

Binary logistic regression was utilized to determine the influence of the EQ-i domain scores on the likelihood of persistence of students on academic probation. Binary logistic regression is an example of a generalized linear model; it is the appropriate type of regression to utilize because it allows the researcher to calculate the likelihood/odds of a dichotomous dependent variable using the most parsimonious model (Menard, 2002). In this case, “persistence to the next semester of college” versus “departure in the next semester of college” was modeled from a set of independent variables that are not required to be normally distributed, linearly related, or of equal variance. The dependent variable was expressed as the log of p/(1-p) (the logit) (Menard, 2002). IBM SPSS Statistics Version 25 was used for all analyses. No student records were missing data and no unusual outlying cases were noted. Additionally, the assumptions of linearity, homoscedasticity, and multicollinearity were met through the analysis of scatterplots and correlations.

Results

To understand the EI factors that increased the likelihood of persistence among students on academic probation for the first time a binary logistic regression was utilized. In the classification table, 88.4% of the cases were classified correctly for persistence, which is an acceptable rate. The independent variables of the model included the EI domain scores, gender, ethnicity, GPA, credits completed, and academic status. Of the explanatory variables of interest, the intrapersonal domain of EI was statistically significant in predicting the likelihood of persistence among students on academic probation. More specifically, when holding all other independent variables constant, a one-unit increase in the EI intrapersonal domain score increased the odds of persisting to the following semester by approximately 17% (B = 0.154, S.E. = .078, p = .047, Exp(B) = 1.166). An additional significant independent variable was academic status. When holding all other independent variables constant, a oneunit increase in academic status (progressing from freshman year to sophomore and so on) multiplied the odds of students persisting to the following semester by nearly six times (B = 1.752, S.E. = .854, p = .038, Exp(B) = 5.768). No other predictors were significant in the model. The Nagelkerke pseudo R2 of the logistic regression model indicated a reasonable goodness of fit, as the model accounted for 35% of the variance in persistence. Refer to Table 2 for the full logistic regression model.

Table 2: Logistic Regression for Model for Predicting Persistence to the Next Semester

Independent Variables B S.E. Wald χ2 P Exp(B)
Intrapersonal EQ-i Domain 0.154 0.078 3.936 0.047* 1.166
Interpersonal EQ-i Domain -0.024 0.049 0.245 0.620 0.976
Stress Management EQ-i Domain 0.014 0.043 0.105 0.746 1.014
Adaptability EQ-i Domain -0.135 0.075 3.265 0.071 0.874
General Mood EQ-i Domain -0.056 0.054 1.059 0.303 0.945
Gender -2.253 1.268 3.155 0.076 0.105
Ethnicity -2.178 1.326 2.697 0.101 0.113
GPA -1.031 0.681 2.292 0.130 0.357
Credits Completed  0.440 0.249 3.120 0.077 1.553
Academic Status  1.752 0.845 4.301 0.038* 5.768
Constant  0.720 6.311 0.013 0.909 0.057

Note. *p < 0.05.

Discussion

This study determined that the intrapersonal domain of EI significantly increased the likelihood of persistence among students on academic probation; for each one-unit increase in the EI intrapersonal domain score, students were nearly 17% more likely to re-enroll at the university the following semester. The intrapersonal domain included dimensions related to self-regard, emotional self-awareness, assertiveness, independence, and self-actualization. Thus, students were assessed on their confidence; the understanding of their emotions; their constructive expression of feelings; and whether they could make responsible, self-directed decisions (Stein et al., 2013). This domain is essential in student development, as it relates to their view of self and can be improved by focusing on developing one’s individuality, boundary setting, and communication skills.

Table 1 indicates students’ scores within the adaptability domain and the general mood domain are at the cusp of the effective functioning cutoff score of 90. Reality testing is a student’s ability to understand reality without interference from emotions. Problem solving is a student’s ability to solve problems and issues without emotional interference, and optimism is having hope for the future. The mean scores were 90.86, 91.13, and 91.67, respectively. These scores were the lowest overall of all the scales. Students with low optimism and reality testing scores tend to perceive the world in a more pessimistic manner, thereby allowing negative emotions to skew their perspectives. When students’ problem-solving scores are lower, it is indicative of poor decision-making. They make impulsive decisions without thinking through the problem to find an appropriate solution. The combined lower scores in these sub-scales may interfere with a student’s ability to persist. As found by Leedy and Smith (2012), the results also suggest these students may lack life experiences that would have enabled them to gain adaptive and optimistic thinking behaviors.Lower scores within the intrapersonal domain are an indication that students typically are unaware of their emotions’ effect on them personally (e.g., they do not possess a deep understanding of the reason they feel a particular way in a given situation), which suggests others may be able to take advantage of them. Further, they are unable to communicate their emotions to others. Decisions by students with lower intrapersonal scores typically are made because of emotions rather than objective reasoning and experience. Additionally, those with low scores in this domain may not view themselves positively and may have difficulty in realizing their potential. These results are in line with other research that has found a relationship between EI and academic success, which indicates greater emotional adjustment problems are seen in students who struggle academically (Afolabi et al., 2009; Houghton et al., 2012; Keefer et al., 2018; Keefer et al., 2012; Salovey et al., 1995).

Limitations and Future Research Opportunities

The greatest limitation to this analysis was the small, non-randomized sample. An ideal sample size for the binary logistic regression would have been 10 events per variable in the model (Wynants et al., 2015). Consent forms, as outlined in the approved IRB protocol, were difficult to obtain from the students; embedding the consent forms within the assessment would have increased the sample size. Students also were invited to meet with an EQ-i coach to review the results and to ask any questions regarding the assessment. All 69 cases met with a coach. Despite issues with scheduling and determining a time to take the assessment, most students revealed it was accurate, useful, and worth their time and energy. All were grateful to be able to understand their EI behaviors, and particularly the ways in which their EI related to their academic success. Future observational research on debriefing sessions, as well as interviews or focus groups with students on their debriefing experiences, would yield rich data on the efficacy and value of the sessions.

Although the instrument was statistically valid and reliable, researchers in this study were unable to control the student fidelity in completing the assessment. Additionally, the costs of administering and debriefing the MHS EQ-i 2.0 Higher Education Assessment can be prohibitive when factoring in the assessment costs and the need for EQ-i certified coaches to provide the debriefing sessions. However, with this sample the benefits far outweighed the costs, as the participants persisted to a greater degree than those who did not take part in the study. Additional research is needed across student groups, such as minoritized students, given the potential for EI testing to aid in students’ understanding of their strengths and areas for enrichment, as well as the effect of EI on academic persistence and overall student success. Further exploration into why the EQ-i intrapersonal domain was found to be a significant predictor for persistence among students on academic probation for the first time could provide deeper insight into the ways in which to increase this skill set among this population. It would also be prudent to test for replicability across other student populations considered to be at risk for departing higher education, as well as focus on outlier students and their experiences.

Recommendations for Practice

If the premise of higher education is to retain students and to ensure all are academically successful, colleges and universities should focus on retention strategies that include noncognitive attributes, particularly for those most at risk for attrition. This can begin with targeted EI programming and support services for students on academic probation. In this case, embedding opportunities for students to enhance their intrapersonal skills and abilities while enrolled in the academic probation course could prove to be valuable. For example, students could be required to keep a journal to document their experiences and feelings over the course of the semester to become more aware of how their emotions interact with their daily highs and lows. They could also conduct a personal SWOT (strengths, weaknesses, opportunities, and threats) analysis and/or complete inventories on their personality, interests, etc. to gain a deeper introspective insight about themselves. Last, students could engage in collaborative group projects that allows them to take on different roles within the group to leverage their strong points and address their shortcomings. Purposefully including strategies for increasing one’s intrapersonal skills will certainly be of great benefit to students, and it could also demonstrate benefits to institutions interested in improving their retention rates.

Pritchard and Wilson (2003) suggested that, when institutions fail to properly attend to non-cognitive issues such as EI and focus only on cognitive matters, they miss students who depart from college for non-academic reasons. Awareness of these factors can be invaluable to postsecondary institutions that seek to lower attrition rates and may aid in the creation of effective programs that assist students who struggle to adjust to collegiate life. These include transitional programs such as mentoring and first-year initiatives. Additionally, wrap-around resources focused on assisting students with low functioning EI scores are as important as other traditional academic interventions (Balduf, 2009; DeAngelo, 2014; Habley et al., 2012; Tinto, 2012). Relevant resources and services involve counseling, wellness and recreation, and academic and career advising. These programs support the possibility of offering systematic EI teaching and learning experiences in postsecondary education.

In this study, EI influenced persistence among students on academic probation; therefore, higher education institutions should consider assessing students’ EI to determine the ways in which institutions can plan and implement curricular and co-curricular initiatives that encourage retention. Most researchers have agreed that students who can manage their emotions are able to persist and to raise their levels of academic achievement because they possess an awareness of their ability to manage the pressures of an academic atmosphere (e.g., test anxiety, fear of failure, low self-confidence) (Afolabi et al., 2009; Houghton et al., 2012; Keefer et al., 2018; Keefer et al., 2012; Mega et al., 2014; Morales, 2008; Noor & Hanafi, 2017; Parker et al., 2006; Ruiz-Aranda et al., 2012; Saklofske et al., 2012; Salovey et al., 1995). Expanding EI assessment to all students, rather than only those at risk for attrition, may be useful in helping with the delivery of necessary services (e.g., mental health counseling, financial aid counseling) in a proactive rather than reactive manner (DeAngelo, 2014; Habley et al., 2012; Tinto, 2012; Whiteman et al., 2013).

Conclusion

Research of this nature is needed in order to dissect the complex challenges faced by students when entering postsecondary education institutions. As demonstrated in this study, EI skills, specifically intrapersonal skills, play an important role in the persistence of college students, a one-unit increase in the intrapersonal domain score significantly increased the odds of persisting to the following semester by approximately 17%. As Tinto (2012) and others have suggested, student affairs administrators and faculty members can aid in reducing departure rates through ensuring students integrate academically, emotionally, and socially into college life by meeting both their educational and personal needs. From a policy perspective, if access for all is a serious goal, postsecondary education administrators must pay closer attention to these EI attributes and must begin to redistribute resources to address holistically the noncognitive measures that influence persistence, retention, and overall student success.

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